M. Elad, Sparse and redundant representations: from theory to applications in signal and image processing, 2010.
DOI : 10.1007/978-1-4419-7011-4

E. J. Candès, Compressive sampling, Proceedings of the International Congress of Mathematicians: Madrid, 2006.
DOI : 10.4171/022-3/69

E. J. Candès, J. Romberg, and T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information, IEEE Transactions on Information Theory, vol.52, issue.2, p.489, 2006.
DOI : 10.1109/TIT.2005.862083

D. L. Donoho, Compressed sensing, IEEE Transactions on Information Theory, vol.52, issue.4, p.1289, 2006.
DOI : 10.1109/TIT.2006.871582
URL : https://hal.archives-ouvertes.fr/inria-00369486

W. L. Chan, A single-pixel terahertz imaging system based on compressed sensing, Applied Physics Letters, vol.93, issue.12, p.12105, 2008.
DOI : 10.1063/1.2989126

M. F. Duarte, Single-Pixel Imaging via Compressive Sampling, IEEE Signal Processing Magazine, vol.25, issue.2, pp.83-91, 2008.
DOI : 10.1109/MSP.2007.914730
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.132.703

J. Hunt, Metamaterial Apertures for Computational Imaging, Science, vol.339, issue.6117, pp.310-313, 2013.
DOI : 10.1126/science.1230054

L. Jacques, CMOS compressed imaging by Random Convolution, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.1113-1116, 2009.
DOI : 10.1109/ICASSP.2009.4959783

O. Katz, Compressive ghost imaging, Applied Physics Letters, vol.95, issue.13, p.131110, 2009.
DOI : 10.1063/1.3238296

A. Levin, Image and depth from a conventional camera with a coded aperture, ACM Transactions on Graphics, vol.26, issue.3, p.70, 2007.
DOI : 10.1145/1276377.1276464

P. Potuluri, M. Xu, and D. Brady, Imaging with random 3D reference structures, Optics Express, vol.11, issue.18, pp.2134-2141, 2003.
DOI : 10.1364/OE.11.002134

C. Zhao, Ghost imaging lidar via sparsity constraints, Applied Physics Letters, vol.101, issue.14, p.141123, 2012.
DOI : 10.1063/1.4757874
URL : http://arxiv.org/abs/1203.3835

D. Shrekenhamer, C. M. Watts, and W. J. Padilla, Terahertz single pixel imaging with an optically controlled dynamic spatial light modulator, Optics Express, vol.21, issue.10, pp.12507-12518, 2013.
DOI : 10.1364/OE.21.012507

H. T. Chen, Active terahertz metamaterial devices, Nature, vol.88, issue.7119, pp.597-600, 2006.
DOI : 10.1038/nature05343

I. M. Vellekoop and A. P. Mosk, Focusing coherent light through opaque strongly scattering media, Optics Letters, vol.32, issue.16, pp.2309-2311, 2007.
DOI : 10.1364/OL.32.002309
URL : http://doc.utwente.nl/71717/1/Vellekoop07focusing.pdf

I. M. Vellekoop, A. Lagendijk, and A. P. Mosk, Exploiting disorder for perfect focusing, Nature Photonics, vol.79, pp.320-322, 2010.
DOI : 10.1038/nphoton.2010.3

R. Pappu, R. Recht, J. Taylor, and N. Gershenfeld, Physical One-Way Functions, Science, vol.297, issue.5589, pp.2026-2030, 2002.
DOI : 10.1126/science.1074376
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.83.6166

S. F. Cotter, Sparse solutions to linear inverse problems with multiple measurement vectors, IEEE Transactions on Signal Processing, vol.53, issue.7, pp.2477-2488, 2005.
DOI : 10.1109/TSP.2005.849172

L. Li and F. Li, Compressive Sensing Based Robust Signal Sampling, Applied Physics Research, vol.4, issue.1, p.30, 2012.
DOI : 10.5539/apr.v4n1p30
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.468.108

A. Goetschy and A. D. Stone, Filtering Random Matrices: The Effect of Incomplete Channel Control in Multiple Scattering, Physical Review Letters, vol.111, issue.6, p.63901, 2013.
DOI : 10.1103/PhysRevLett.111.063901

R. Gribonval, G. Chardon, and L. Daudet, Blind calibration for compressed sensing by convex optimization, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.2713-2716, 2012.
DOI : 10.1109/ICASSP.2012.6288477
URL : https://hal.archives-ouvertes.fr/hal-00658579

S. M. Popoff, Measuring the Transmission Matrix in Optics: An Approach to the Study and Control of Light Propagation in Disordered Media, Physical Review Letters, vol.104, issue.10, p.100601, 2010.
DOI : 10.1103/PhysRevLett.104.100601
URL : https://hal.archives-ouvertes.fr/hal-00448285

S. M. Popoff, Controlling light through optical disordered media: transmission matrix approach, New Journal of Physics, vol.13, issue.12, p.123021, 2011.
DOI : 10.1088/1367-2630/13/12/123021
URL : https://hal.archives-ouvertes.fr/hal-00611018

Y. C. Eldar and . Kutyniok, Compressed sensing: theory and applications, 2012.
DOI : 10.1017/CBO9780511794308

E. J. Candès and M. B. Wakin, An Introduction To Compressive Sampling, IEEE Signal Processing Magazine, vol.25, issue.2, pp.21-30, 2008.
DOI : 10.1109/MSP.2007.914731

R. Tibshirani, Regression shrinkage and selection via the lasso, J. Roy. Stat. Soc. B Met, pp.267-288, 1996.

H. Ohlsson, Compressive phase retrieval from squared output measurements via semidefinite programming. arXiv, 1111, p.6323, 2011.

D. Donoho and J. Tanner, Precise Undersampling Theorems, Proc. IEEE 98, pp.913-924, 2010.
DOI : 10.1109/JPROC.2010.2045630

E. Akkermans, Mesoscopic physics of electrons and photons, 2007.
DOI : 10.1017/CBO9780511618833

E. J. Candès, The restricted isometry property and its implications for compressed sensing, Comptes Rendus Mathematique, vol.346, issue.9-10, pp.589-592, 2008.
DOI : 10.1016/j.crma.2008.03.014

A. Cohen, W. Dahmen, and R. Devore, Compressed sensing and best $k$-term approximation, Journal of the American Mathematical Society, vol.22, issue.1, pp.211-231, 2009.
DOI : 10.1090/S0894-0347-08-00610-3

W. Yin and Y. Zhang, Extracting salient features from less data via l1-minimization. SIAG/OPT Views-and-News 19, pp.11-19, 2008.

D. L. Donoho and X. Huo, Uncertainty principles and ideal atomic decomposition, IEEE Transactions on Information Theory, vol.47, issue.7, pp.2845-2862, 2001.
DOI : 10.1109/18.959265
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.9300

J. A. Tropp, Greed is Good: Algorithmic Results for Sparse Approximation, IEEE Transactions on Information Theory, vol.50, issue.10, pp.2231-2242, 2004.
DOI : 10.1109/TIT.2004.834793

J. A. Tropp and A. C. Gilbert, Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit, IEEE Transactions on Information Theory, vol.53, issue.12, pp.4655-4666, 2007.
DOI : 10.1109/TIT.2007.909108
URL : http://authors.library.caltech.edu/9490/1/TROieeetit07.pdf

J. Wang and B. Shim, A Simple Proof of the Mutual Incoherence Condition for Orthogonal Matching Pursuit, p.4408, 2011.

E. J. Candès, Compressed sensing with coherent and redundant dictionaries, Applied and Computational Harmonic Analysis, vol.31, issue.1, pp.59-73, 2011.
DOI : 10.1016/j.acha.2010.10.002

S. M. Popoff, Image transmission through an opaque material, Nature Communications, vol.41, issue.6, p.81, 2010.
DOI : 10.1038/ncomms1078
URL : https://hal.archives-ouvertes.fr/hal-00524487

R. Gribonval, Atoms of All Channels, Unite! Average Case Analysis of??Multi-Channel Sparse Recovery Using Greedy Algorithms, Journal of Fourier Analysis and Applications, vol.86, issue.3, pp.655-687, 2008.
DOI : 10.1007/s00041-008-9044-y
URL : https://hal.archives-ouvertes.fr/inria-00146660

D. Donoho and J. Tanner, Observed universality of phase transitions in highdimensional geometry, with implications for modern data analysis and signal processing, pp.4273-4293, 2009.

Y. Eldar and H. Rauhut, Average Case Analysis of Multichannel Sparse Recovery Using Convex Relaxation, IEEE Transactions on Information Theory, vol.56, issue.1, pp.505-519, 2010.
DOI : 10.1109/TIT.2009.2034789

O. Katz, Non-invasive real-time imaging through scattering layers and around corners via speckle correlations. arXiv, 1403, p.3316, 2014.